How to create new dataframe by filtering a column of another dataframe

Question

I have a few datasets that share the same columns so I concatenated them together to form one large dateframe. My idea is to filter a goals_per_90 column by > .5 so it will create a new dataframe showing those whole rows of all the players with a value greater than .5 in a new dataframe. Im thinking of something like this at the moment but getting stuck when

 def gettopplayers(Dataframe):
   if Dataframe.loc[Dataframe['goals_per_90_overall'] > .5]:
     apply.

Im getting lost as to where to append this row to. Any help would be greatly appreciated. Thank you!

Adding minimal example with expected output may be helpful for others to answer. — niraj
– niraj, Commented Aug 21, 2020 at 20:02
If you are trying to create a new DataFrame by filtering rows of another Dataframe returning the df.loc[condition] will do the job — Ariyan
– Ariyan, Commented Aug 21, 2020 at 20:05

Shaido · Accepted Answer · 2021-06-22 07:58:56Z

3

Below python code will make a new dataframe with all the rows where the condition is met. No need for the if condition.

df_new = Dataframe.loc[(Dataframe['goals_per_90_overall'] > .5)]

edited Jun 22, 2021 at 7:58

Shaido

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answered Aug 22, 2020 at 6:33

Aagam Sheth

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2 Comments

TechNewbie Over a year ago

Hi, can you explain what loc is doing here: [(Dataframe['goals_per_90_overall'] > .5)]? I am struggling to understand how to use loc but, I see it so much with pandas.

Aagam Sheth Over a year ago

@TechNewbie The Dataframe['goals_per_90_overall'] > .5 produces a tuple of boolean values meeting the following condition. DF.loc() takes the tuple as input and returns the entire rows with corresponding index. loc is usually label based but can be used with booleans as in the above example. The best source for Pandas learning is the documentation pandas.pydata.org/pandas-docs/stable/reference/api/…

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